In a scene from the movie Gladiator, Roman emperor Marcus Aurelius, worried about the fragility of his empire, tells his general, Maximus: “There was once a dream that was Rome. You could only whisper it. Anything more than a whisper and it would vanish.”
The same could be said qubits. They are foundational components of quantum computers, and are one of thornier challenges in getting stable and usable systems up and running. A key reason is how fragile they are and how easily they can lose their quantum states (also known as “decoherence”). They are highly sensitive to any number of disturbances in their environment, from temperature, vibration, and sound to electromagnetic fields, pressure changes, and stray particles.
Any of these can cause errors during computation, which puts a premium on error correction. Without it, creating a fault-tolerant, reliable quantum system that can solve highly complex commercial and scientific quantum calculations is nigh impossible.
That said, there have been remarkable strides in recent months in addressing the error correction conundrum.
Bigger Steps Coming Faster
Scientists with Google’s Quantum AI Lab in December unveiled Willow, the company’s latest quantum chip that leverages its breakthrough that essentially involves pulling together many physical qubits – creating a “logical qubit” – that work together to correct errors.
Earlier this month, Microsoft researchers announced Majorana, a quantum chip that they said accelerates the timeline for creating a usable quantum system from decades to years. The new chip is based on quasiparticles, which for almost a century had been a theory. However, they said quasiparticles now can be created and controlled on demand by topoconductors, all of which makes them ideal for qubits.
Now comes Amazon Web Services with Ocelot, a quantum chip developed at the AWS Center for Quantum Computing at the California Institute of Technology that the cloud builder claims not only addresses the error correction challenge but can also reduce the costs of implementing error correction by as much as 90 percent.
“We believe that scaling Ocelot to a full-fledged quantum computer capable of transformative societal impact would require as little as one-tenth as many resources as common approaches, helping bring closer the age of practical quantum computing,” Oskar Painter, director of quantum hardware, and Fernando Brandão, director of applied science, at AWS, wrote in a column.
Painter added via another blog post that “concretely, we believe this will accelerate our timeline to a practical quantum computer by up to five years.”
Ocelot Enters The Scene
Ocelot, which is a research prototype detailed in a paper published this week in Nature, represents Amazon’s first stab at creating a hardware implementation of error correction in quantum systems. That implementation in hardware is a key part of not only creating a practical quantum system, but also one that reduces its costs enough to make it economically viable.
Painter and Brandão wrote that AWS’ research addresses three key areas: creating a scalable architecture for bosonic error correction, using a noise-biased gate that can lead to hardware-based error correction, and accelerating the performance of superconducting qubits.
Methods being developed to address error correction is driving a lot of the costs in quantum systems, using requiring thousands – and may be hundreds, in the future – of physical qubits per logical one, they wrote. In that scenario, a workable quantum computer would need millions of physical qubits, far exceeding the qubit count of current systems.
A reason is that quantum systems need to deal with two kinds of errors, bit-flip errors that also are found in bits used in classical computers and phase-flip errors, which are only in qubits. Given that, quantum systems need to address both types. AWS is using cat qubits, which the researchers wrote suppress certain forms of errors, which in turn reduces the resources – and associated costs – needed for quantum error correction, which paves the path to both scalable and less-costly quantum systems.
“Cat qubits use the quantum superposition of classical-like states of well-defined amplitude and phase to encode a qubit’s worth of information,” they wrote. “A major advantage of cat qubits is their inherent protection against bit-flip errors. Increasing the number of photons in the oscillator can make the rate of the bit-flip errors exponentially small. This means that instead of increasing qubit count, we can simply increase the energy of an oscillator, making error correction far more efficient.”
Addressing Two Kinds Of Errors
The AWS team essentially used five cat qubits (each with an oscillator to store quantum data) to create a logical qubit that addressed errors, as seen below. Bit-flip errors were suppressed at the physical qubit level, while phase-flip errors were corrected using a repetition code, which they called the simplest classical error-correcting code. In addition, “highly noise-biased controlled-NOT (C-NOT) gates, between each cat qubit and ancillary transmon qubits (the conventional qubit used in superconducting quantum circuits), enable phase-flip-error detection while preserving the cat’s bit-flip protection.”
“Ocelot represents our first chip with the cat qubit architecture, and an initial test of its suitability as a fundamental building block for implementing quantum error correction,” Painter and Brandão wrote. “Future versions of Ocelot are being developed that will exponentially drive down logical error rates, enabled by both an improvement in component performance and an increase in code distance.”
In the AWS blog post, Painter wrote that it was important that AWS built Ocelot with error correction built in rather than added on.
“We looked at how others were approaching quantum error correction and decided to take a different path,” Painter wrote. “We didn’t take an existing architecture and then try to incorporate error correction afterwards. We selected our qubit and architecture with quantum error correction as the top requirement. We believe that if we’re going to make practical quantum computers, quantum error correction needs to come first.”
A View Of The Future
How much Ocelot, Willow, and Majorana accelerate the time to a fault-tolerant and practical quantum computer remains to be seen. There are more than a few doubters who still measure that time in decades. That said, many parts of the tech industry are moving forward under the belief that it will be sooner.
That can be seen in efforts by Google and others to develop and deploy post-quantum cryptography technology to protect sensitive data against cybercriminals who may use the massive power of quantum systems to blow through modern encryption techniques, as well D-Wave’s expanding business around its Advantage annealing quantum computers. Also this week, quantum company PSIQuantum in a paper in Nature introduced Omega, a quantum photonic chipset that included the advanced components needed to build systems with millions of qubits.
“What sets us apart is the manufacturability and connectivity of our hardware,” PSIQuantum co-founder and chief technologist Mark Thompson said in a statement. “Our technology is manufactured in a high-volume semiconductor fab that normally produces chips for cell phones and the automotive industry and now yields the world’s highest-performance photonic qubits. We can also seamlessly connect our chips together using conventional optical fibers, allowing us to rapidly scale-up our systems and deliver truly powerful quantum computers.”